Neural Network Loss Function: Mean (absolute) Cubic Error

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ThomasP
ThomasP 2022-3-21
编辑： ThomasP 2022-3-21
Hello,
for my neural network, it's very important to not have a high error-range, i.e. a higher mean-error is better than a higher error-range.
That's why I'd like to implement a different loss function. My network has a regressionLayer Output which computes loss based on mean squared error. To increase the weight of errors that lie further away, I'd like to change that into a mean cubic error.
The standard loss function of the regression Layer is and I'd like to perform a tiny change to or alternatively .
Is that possible in a not so complicated way?
Thank you for your help in advance,
Best regards

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回答（1 个）

Torsten
Torsten 2022-3-21
You want the error to be negative if t_i < y_i ?
This won't work: The loss function should always be non-negative.

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